code: def _save_runnables(model, path, loader_fn=None, persist_dir=None):
      model_data_kwargs = {_MODEL_LOAD_KEY: _RUNNABLE_LOAD_KEY}
      if isinstance(model, lc_runnable_with_steps_types()):
          model_data_path = _MODEL_DATA_FOLDER_NAME
          _save_runnable_with_steps(
              model.steps,
              os.path.join(path, model_data_path),
              loader_fn,
              persist_dir,
          )
      elif isinstance(model, picklable_runnable_types()):
          model_data_path = _MODEL_DATA_PKL_FILE_NAME
          _save_picklable_runnable(
              model, os.path.join(path, model_data_path)
          )
      elif isinstance(model, lc_runnable_branch_type()):
          model_data_path = _MODEL_DATA_FOLDER_NAME
          _save_runnable_branch(
              model,
              os.path.join(path, model_data_path),
              loader_fn,
              persist_dir,
          )
      else:
          raise MlflowException.invalid_parameter_value(
              _UNSUPPORTED_MODEL_ERROR_MESSAGE.format(
                  instance_type=type(model).__name__
              )
          )
      model_data_kwargs.update({_MODEL_DATA_KEY: model_data_path})
      return model_data_kwargs
  
file_path: mlflow/mlflow/langchain/runnables.py
imports: import os
  from pathlib import Path
  from typing import Union
  import cloudpickle
  import yaml
  from mlflow.exceptions import MlflowException
  from mlflow.langchain.utils import _BASE_LOAD_KEY, _CONFIG_LOAD_KEY, _MODEL_DATA_FOLDER_NAME, _MODEL_DATA_KEY, _MODEL_DATA_PKL_FILE_NAME, _MODEL_DATA_YAML_FILE_NAME, _MODEL_LOAD_KEY, _MODEL_TYPE_KEY, _RUNNABLE_LOAD_KEY, _UNSUPPORTED_MODEL_ERROR_MESSAGE, _load_base_lcs, _load_from_json, _load_from_pickle, _load_from_yaml, _save_base_lcs, _validate_and_wrap_lc_model, base_lc_types, custom_type_to_loader_dict, lc_runnable_branch_type, lc_runnable_with_steps_types, lc_runnables_types, picklable_runnable_types
label_desc: Use image node_id 10 for calling a global function with example usage: _save_runnables(model, path, loader_fn, persist_dir) and returns: model_data_kwargs